MSc. SET Theses and Dissertations (2025)

Permanent URI for this collection

http://hdl.handle.net/11071/15968

Browse

Now showing 1 - 7 of 7

Modeling carbon emission from cooking fuels in rural communities: a pathway to low-carbon emission
(Strathmore University, 2025) Rono, B. C.
The availability of clean, sustainable cooking fuel remains a fundamental obstacle throughout Kenyan rural areas since traditional biomass fuels like firewood and charcoal control household energy usage patterns. Using these fuels causes significant carbon pollution, deforestation damage, and health risks from indoor air contamination. The transition must establish low-carbon energy alternatives for effective change between environmental responsibility and reasonable cost-effectiveness. This research evaluates carbon emissions across cooking fuel types within Kenyan rural areas while identifying methods to decrease emissions. The analysis uses Microsoft Excel Software to evaluate four energy transition strategies, from Business-As-Usual (BAU) through Liquefied Petroleum Gas (LPG) use and bioethanol and electricity combination to an extensive clean energy implementation. The study presents data-driven emission projections that combine literature research with energy consumption surveys and policy guidelines for different intervention approaches. The KNBS data shows that cooking fuel emissions will increase because of population expansion and the continued use of biomass in the Business-As-Usual context. The complete electrification of cooking equipment offers the most lasting solution against emissions reduction since it effectively surpasses LPG and bioethanol systems. The transition to sustainable cooking needs improvements in infrastructure systems, a solution for affordability, and better policy enforcement. The investigation demonstrates the pressing requirement for government-backed programs, financial resources from the private sector, and active community participation to enhance clean cooking technology adoption rates. Governments should provide financial support for green energy fuels, develop expanded power grid systems, and launch information programs to change public cooking behavior. Implementing such measures will lead rural communities towards sustainable, low-carbon cooking solutions that support countrywide and global climate objectives.
Modelling of municipal solid waste use for steam generation for industrial and hospitality sector
(Strathmore University, 2025) Omare, J. W.
The cumulative demand for steam in the hospitality and industrial sectors has led to rising financial and environmental costs due to the prevalent use of biomass for steam generation. This challenge has intensified by issues such as resource depletion, competition for land with food crops, and the bulky nature of biomass, which complicates energy management. Previous attempts to use Municipal Solid Waste (MSW) as an alternative fuel for steam generation have yielded inconclusive results, underscoring the need for further research to establish its feasibility as a replacement for biomass. This study modeled the use of MSW for steam generation in industrial and hospitality sectors. The main objective of this study was to model transport and treatment processes in MSW steam generation. Secondary data was collected from three zones in Nairobi, an industry setup and a hotel, each characterized by different energy & waste profiles stemming from varied commercial and social activities. The data collected was analyzed using a developed model incorporating governing equations for calorific value calculations, transport, treatment, and the Levelized Cost of Steam (LCOS). Under three scenarios, the calorific values of MSW and biomass (Eucalyptus globulus) were analyzed, revealing that MSW possessed a superior energy density at 23.80 MJ/kg compared to biomass at 17.34–17.43 MJ/kg. Proximate analysis of Nairobi’s MSW highlighted organic waste dominates at 65.4% of the total waste and moisture content was reduced from 19.03% to 15% via drying to enhance combustion efficiency. Also, transportation costs were modeled for two collection points, emphasizing distance-driven variations. The techno-economic framework computed the LCOS by integrating capital and operational expenditures, as well as transport and treatment costs. Results demonstrated the cost-effectiveness of MSW, with LCOS values of 1.48–1.49 Ksh/kg and 2.24–2.32 Ksh/kg for the two companies analyzed respectively. This shows 25–26% reduction over biomass. Scenario analyses confirmed MSW’s resilience to cost escalations, as it maintained lower costs than biomass. Although costs varied non-linearly with transportation and drying, the processes added more operational annually, but the overall LCOS remained economically viable, compared to biomass. MSW reduced feedstock demand by 27% and storage requirements, thereby aligning with Kenya’s waste management and renewable energy goals. The proposed model offered a replicable framework for optimizing MSW utilization in steam generation, emphasizing localized waste characterization and policy cost incentives. Recommendations include advancing waste-to-energy conversion studies, spatial transport optimization, and the integration of social economic factors in future models. These findings supported the adoption of MSW to mitigate production costs, reduce deforestation, and foster sustainable urban energy transitions.
Optimized renewable energy powered irrigation system using mathematical programming: a case study for Kiserian, Kenya
(Strathmore University, 2025) Juma, S.
Energy supply for irrigation in remote areas has been a challenge. Energy is needed to support agricultural activities like pumping water required to enhance crop development and growth in areas that receive less rainfall. There have been efforts to expand the grid for universal access. However, it has been proven to be costly to extend the grid network to remote areas. A suggested solution is to use decentralized systems such as wind and solar. They are affordable, clean sources of energy and readily available. They are affordable, clean sources of energy and readily available. This approach could work well, however, there is insufficiency of data that could help decision makers to settle on the most appropriate solutions. This creates a need for researchers to innovatively develop more data on how solar and wind resources could be optimized for energy applications in agriculture. This study looked at the optimization of solar photovoltaic and wind turbines to pump water for irrigation as a hybrid system that could be utilized at Kiserian, Kajiado county. Tomato crops were used to determine the energy needed to supply water on a hectare piece of land. A hybrid energy system of solar PV and wind turbine was designed using an Equilibrium Optimizer (EO) algorithm and simulated using MATLAB R2024b software. The model was used to perform the net present cost of the integrated system to generate the optimal result. Then the levelized cost of energy was determined to assess the economic performance of hybrid system. The results were compared with standalone solar PV and wind turbines. The study revealed that it was economical for small-scale farmers to power an irrigation system using solar PV as a standalone, and the hybrid of solar PV and wind turbine would work well for large scale farmers. Keywords: Renewable energy system, solar photovoltaic, wind turbine, Equilibrium Optimizer Algorithm, Net Present Cost, Levelized Cost of Energy and Optimization.
Decarbonization of urban road infrastructure using solar street lighting in Kenya: assessing implementation and impact
(Strathmore University, 2025) Mabonga, P. S.
Decarbonizing urban road infrastructure using solar street lighting is a very promising perspective for the sustainable development of Kenya. This dissertation deals with a comprehensive study investigating the implementation and impacts of solar-powered lighting system adoption in urban areas, taking Mombasa City’s southern bypass highway as a case study. The fact that warrants the transition is that the benefits are manifold, such as reduced greenhouse gas emissions, increased energy efficiency, better public safety, and economic savings in running and maintaining lighting systems. However, the potential of solar street lighting has several limitations and assumptions that require empirical research to evaluate its feasibility and effectiveness. The dissertation design is based on a comprehensive literature review to consolidate the current knowledge on solar street lighting, followed by a detailed methodology based on data collection, model development, and data analysis. The Mombasa Southern Bypass case study has helped us understand the local context, considering regulatory frameworks, technological requirements, and socioeconomic factors. The research, by running a qualitative and quantitative investigation about the main technical, economic, and regulatory issues arising from the implementation of solar street lighting, aimed to estimate the impacts that the sustainable infrastructure solution has on urban planning, energy consumption, and environmental quality to orient the definition of the potential advantages and disadvantages for policymakers, urban planners, and other stakeholders in implementing such solutions. The way forward is to gather findings from the outcomes of this research, which aided in developing evidence-based mechanisms to achieve decarbonization and sustainable urban development in Kenya and beyond. The study found that while street lighting infrastructure in Mombasa City is functional, significant improvements are needed, with a predominant reliance on conventional lighting technologies like incandescent and fluorescent lamps. In addition, the study found that solar street lighting is viable in Mombasa, and the irradiation level is sufficient to maintain reliable operation. The study identified several barriers to adopting solar street lighting in Kenya, including high initial costs, insufficient technical expertise, inadequate infrastructure, limited local solar technology availability, and logistical challenges. It also highlights the lack of government incentives, public resistance, and financing issues as significant obstacles to widespread adoption. Further, the study revealed that adopting solar street lighting in urban areas, including Mombasa City, is expected to reduce energy consumption and carbon emissions. The study recommends transitioning to solar-powered lighting technologies in Mombasa City and the rest of the country to reduce energy consumption and emissions. It suggests integrating sustainable lighting into urban planning, investing in local solar technology adoption, and developing financing mechanisms to overcome financial barriers. Additionally, it emphasizes strengthening local capacity through training, streamlining approval processes, and increasing awareness campaigns to address public resistance and ensure the successful implementation of solar street lighting projects.
Renewable Energy-Based Hybrid Power Systems for off-grid Base Transceiver Stations - a case study of BTS site in Kajiado County
(Strathmore University, 2025) Kiarie, A. B
This study explores the technical and economic feasibility of deploying a renewable hybrid power system comprising solar photovoltaic (PV), battery storage, and hydrogen fuel cells for powering off-grid Base Transceiver Stations (BTS) in Kenya. Motivated by the environmental impact and high operational costs of diesel generators currently used as backup power sources in telecommunications infrastructure, the research proposes an alternative energy solution aligned with Kenya’s carbon reduction targets under the Nationally Determined Contributions (NDC). A case study of a BTS site in Kajiado County was used to evaluate the proposed hybrid configuration. The system was modelled and simulated using MATLAB/Simulink to assess power flow, fuel cell activation, battery state of charge, and solar irradiance behaviour. HOMER software was used for system optimization and economic analysis, incorporating real load data, solar resource inputs, and cost parameters. Results indicate that the hybrid system meets energy demands reliably, with solar PV supplying most of the energy, batteries stabilizing supply, and the proton exchange membrane fuel cell (PEMFC) acting as a backup. The proposed system achieves an annual electricity output of approximately 67.43 MWh, with a Levelized Cost of Electricity (LCOE) of $0.351/kWh and a Net Present Cost (NPC) of $87,404 lower than the $102,253 NPC of a diesel-based system. Additionally, the system significantly reduces carbon emissions and fuel dependency. The findings demonstrate that integrating hydrogen fuel cells with solar and battery systems can provide a sustainable, cost-effective power solution for off-grid telecom sites. The study supports broader adoption of clean energy in Kenya’s telecommunications sector and contributes to climate action and energy access goals.
Assessment of sustainable electricity generation scenarios in Burundi using multi-criteria approaches
(Strathmore University, 2025) Igiraneza, N. L.
With an 11% electrification rate, Burundi is one of the countries in the sub-Saharan region still facing significant energy access challenges in the region. This has considerably impacted the economic development, energy security and technical advancement of the country. The country primarily relies on hydroelectric power, with 49MW installed out of a potential 1700MW, as well as diesel thermal plants, solar, biomass, peat, firewood, coal, bagasse, although on a smaller scale. Due to a poor energy mix and inadequate maintenance of existing hydro infrastructure, technical issues, like insufficient capacity, supply disruptions lead to low-quality electrical supply. Moreover, the increasing reliance on traditional biomass has led to deforestation, and environmental degradation. There have been nevertheless attempted initiatives to close the energy supply and demand imbalance, while promoting renewable energy integration. Burundi is boosting energy generation through public and private initiatives, including rehabilitating existing hydropower infrastructure, developing rural electrification with mini-hydro, solar, and wind power, extending electric networks and building regional plants with neighbors. Feasibility studies for solar and wind power investments are also in progress. Despite this, there is no data and structured modeling tool available to support evidence-based decisions about these investments. This study aimed to assess the pathways to electricity generation by developing and testing an energy planning tool, that integrated available resources and the future energy demand in Burundi, to close the existing gap between supply and demand. It will serve as a resource for the relevant stakeholders as they tackle the issues of energy access, affordability, security, decarbonization and decentralization, and support potential investors in their decision making.
A Model for estimating the state of health of retired lithium-ion EV batteries based on machine learning
(Strathmore University, 2025) Rugami, V.
The electric vehicle market is growing rapidly and with it comes subsequent growth in the number of lithium-ion batteries that reach end of life in electric vehicle applications. Instead of being discarded in landfills, these batteries can be used in other applications such as energy storage since they still retain about 70% to 80% of their original capacity. This is known as battery repurposing, and it helps to manage battery waste. To repurpose batteries, their state of health must be tested to determine if they are adequately safe and reliable to use in second life applications. Current testing methods are time-consuming. Long testing times inhibit the scalability of repurposing operations to match the rapidly increasing number of electric vehicles, hence retired electric vehicle batteries. In this study, a machine learning model was developed to determine the SOH of used batteries. The model was based on quantum particle swarm optimization-support vector regression (QPSO-SVR) and used partial discharge data from differential capacity curves to estimate SOH. It was trained on data obtained from cycling used battery cells. The model achieved best MAE of 0.6139, RMSE of 0.7875, and R2 of 0.8481.

Browse

Browsing MSc. SET Theses and Dissertations (2025) by Issue Date

Results Per Page

Sort Options